Accepted Posters
Poster abstracts (pdf)
Poster panel size: 165cm (height) x 110cm (width)
P01:
Utilizing Fuzzy-SVM and a Subject Database to Reduce the Calibration Time of P300-based BCI
Sercan Taha Ahi, Tokyo Institute of Technology;
Natsue Yoshimura, Tokyo Institute of Technology;
Hiroyuki Kambara, Tokyo Institute of Technology;
Yasuharu Koike, Tokyo Institute of Technology
P02:
Feature Selection for Reinforcement Learning: Evaluating Implicit State-reward Dependency via Conditional Mutual Information
Hirotaka Hachiya, Tokyo Institute of Technology;
Masashi Sugiyama, Tokyo Institute of Technology
P03:
Dependence Minimizing Regression with Model Selection for Non-linear Causal Inference under Non-Gaussian Noise
Makoto Yamada, Tokyo Institute of Technology;
Masashi Sugiyama, Tokyo Institute of Technology
P04:
Joint Unsupervised Learning of Parallel Sequence Alignment and Segmentation
Mark Fishel, University of Tartu
P05:
Multi-class Subgroup Discovery
Tarek Abudawood, University of Bristol;
Peter Flach, University of Bristol
P06:
A Comparison of CNF with CRF in Named Entity Recognition Task
Kei Uchiumi, Yahoo Japan Corporation;
Keigo Machinaga, Yahoo Japan Corporation;
Toshiyuki Maezawa, Yahoo Japan Corporation;
Toshinori Satou, Yahoo Japan Corporation
P07:
Multiscale-bagging with Applications to Classification
Masayoshi Aoki, Tokyo Institute of Technology;
Takafumi Kanamori, Nagoya University;
Hidetoshi Shimodaira, Tokyo Institute of Technology
P08:
Contrasting Correlations by an Efficient Double-clique Search Method
Aixiang Li, Hokkaido University;
Makoto Haraguchi, Hokkaido University
P09:
Model-induced Regularization
Shinichi Nakajima, Nikon Corporation;
Masashi Sugiyama, Tokyo Institute of Technology
P10:
Slice Sampling on Chinese Restaurant Process
Takaki Makino, University of Tokyo
P11:
Interactive Behavior Adaptation through Dialogue Based on Bayesian Network
Saifuddin Md. Tareeq, The Graduate University for Advanced Studies;
Tetsunari Inamura, National Institute of Informatics
P12:
Maximum Volume Clustering
Gang Niu, Nanjing University;
Bo Dai, Chinese Academy of Science;
Lin Shang, Nanjing University;
Masashi Sugiyama, Tokyo Institute of Technology
P13:
Using Conditional Random Fields to Validate Observations in a 4W1H Paradigm
Leon F. Palafox, University of Tokyo;
Laszlo A. Jeni, University of Tokyo;
Hideki Hashimoto, University of Tokyo
P14:
Multiscale Bagging with Applications to Classification and Active Learning
Hidetoshi Shimodaira, Tokyo Institute of Technology;
Takafumi Kanamori, Nagoya University;
Masayoshi Aoki, Tokyo Institute of Technology;
Kouta Mine, Tokyo Institute of Technology
P15:
Adjustment for Multiple Hypotheses Testing in Comparative Classification Studies
Daniel Berrar, Tokyo Institute of Technology
P16:
Inference in Latent Conditional Models: The Computational Complexity Analysis and a Comparative Study of Solutions
Xu Sun, University of Tokyo;
Hisashi Kashima, University of Tokyo;
Takuya Matsuzaki, University of Tokyo
P17:
Improving Graph-based Semi-supervised Learning by Feature Space Transformation
Yu-Shi Lin, Academia Sinica and National Taiwan University;
Chun-Nan Hsu, Academia Sinica and University of Southern California
P18:
Image Annotation via Multi-instance Learning with Pyramid Graph Kernel
Zhi Nie, Tsinghua University; Guiguang Ding, Tsinghua University;
Chunping Li, Tsinghua University
P19:
Proximity in Large Bipartite Graphs with Unsupervised Auxiliary Information
Rudy Raymond, IBM Research - Tokyo;
Yuta Tsuboi, IBM Research - Tokyo;
Hisashi Kashima, The University of Tokyo;
Issei Sato, The University of Tokyo
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